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medical-research-toolkit医学研究工具包

Agent Skill

medical-research-toolkit 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

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安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:medical-research-toolkit(医学研究工具包)
来源仓库:https://github.com/pascalwhoop/medical-research-toolkit
安装命令:
openclaw skills install medical-research-toolkit
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

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openclaw skills install medical-research-toolkit

简介

用于查询超过 14 个生物医学数据库,支持药物再利用与靶点发现。

  • 可访问 ChEMBL、PubMed 等权威资源,辅助科研决策。
  • 适合在 OpenClaw 中进行临床试验与文献综合分析。
  • 安装命令:openclaw skills install medical-research-toolkit。
  • 建议确认 API 调用频率限制与数据更新周期。

SKILL.md

name
medical-research-toolkit
description
Query 14+ biomedical databases for drug repurposing, target discovery, clinical trials, and literature research. Access ChEMBL, PubMed, ClinicalTrials.gov, OpenTargets, OpenFDA, OMIM, Reactome, KEGG, UniProt, and more through a unified MCP endpoint. Use when researching disease targets, finding approved/investigational drugs, searching clinical evidence, discovering genetic associations, or analyzing compound bioactivity data.

Medical Research Toolkit

Query 14+ biomedical databases for drug repurposing, target discovery, clinical evidence, and literature research — all via a unified MCP endpoint.

⚡ 30-Second Start

# Find drugs for myasthenia gravis
curl -X POST https://mcp.cloud.curiloo.com/tools/unified/mcp \
  -H "Content-Type: application/json" -H "Accept: application/json" \
  -d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"chembl_find_drugs_by_indication","arguments":{"indication":"myasthenia gravis","max_results":10}},"id":1}'

That's it! You now have approved and investigational drugs for the disease.


Quick Recipes

Find Drugs for a Disease

curl -X POST https://mcp.cloud.curiloo.com/tools/unified/mcp \
  -H "Content-Type: application/json" -H "Accept: application/json" \
  -d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"chembl_find_drugs_by_indication","arguments":{"indication":"myasthenia gravis","max_results":20}},"id":1}'

Returns: Approved + investigational drugs with max phase reached

Find Disease Targets

# First: Find disease ID
curl -X POST https://mcp.cloud.curiloo.com/tools/unified/mcp \
  -H "Content-Type: application/json" -H "Accept: application/json" \
  -d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"opentargets_search","arguments":{"query":"myasthenia gravis","entity_type":"disease"}},"id":1}'

# Returns: disease ID (e.g., EFO_0004991)
# Then: Get targets
curl -X POST https://mcp.cloud.curiloo.com/tools/unified/mcp \
  -H "Content-Type: application/json" -H "Accept: application/json" \
  -d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"opentargets_get_associations","arguments":{"disease_id":"EFO_0004991","size":20}},"id":2}'

Returns: Top disease targets ranked by evidence strength (0-1 score)

Search Literature

curl -X POST https://mcp.cloud.curiloo.com/tools/unified/mcp \
  -H "Content-Type: application/json" -H "Accept: application/json" \
  -d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"pubmed_search_articles","arguments":{"diseases":["myasthenia gravis"],"keywords":["immunotherapy"],"max_results":20}},"id":1}'

Returns: PubMed articles on myasthenia gravis immunotherapy

Find Active Clinical Trials

curl -X POST https://mcp.cloud.curiloo.com/tools/unified/mcp \
  -H "Content-Type: application/json" -H "Accept: application/json" \
  -d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"ctg_search_studies","arguments":{"condition":"myasthenia gravis","recruitment_status":"RECRUITING","max_results":20}},"id":1}'

Returns: Actively recruiting trials for the disease

Check Drug Safety

curl -X POST https://mcp.cloud.curiloo.com/tools/unified/mcp \
  -H "Content-Type: application/json" -H "Accept: application/json" \
  -d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"openfda_search_adverse_events","arguments":{"drug_name":"eculizumab","limit":50}},"id":1}'

Returns: FDA adverse event reports—check for serious outcomes, death, hospitalization


What You Get

14+ Integrated Databases

DatabaseWhat's InsideUse For
ChEMBL2M drugs, bioactivity dataFinding approved/investigational drugs
OpenTargetsDisease-target links + evidenceIdentifying therapeutic targets
PubMed35M+ articles + preprintsLiterature review & validation
ClinicalTrials.gov400K+ active trialsFinding ongoing studies
OpenFDAAdverse events, drug labelsSafety assessment
OMIMGenetic diseases, genes → phenotypesUnderstanding disease genetics
ReactomePathways, protein interactionsMechanism understanding
UniProtProtein sequences, annotationsProtein properties
KEGGMetabolic & disease pathwaysSystems-level view
GWAS CatalogGenetic associationsVariant discovery
Pathway CommonsIntegrated pathway dataNetwork analysis
MyGene.infoGene annotationsID mapping
MyVariant.infoVariant effectsVariant interpretation
+ more

Use Cases

🧬 Drug Repurposing

Find non-standard-care drugs for rare/complex diseases:

  1. Find disease targets (OpenTargets)
  2. Search for drugs targeting those genes (ChEMBL)
  3. Check ongoing trials (ClinicalTrials)
  4. Verify safety (OpenFDA, PubMed)

🔬 Target Discovery

Identify novel therapeutic targets:

  1. Find disease associations (OpenTargets, GWAS)
  2. Get pathway context (Reactome, KEGG)
  3. Review literature (PubMed)
  4. Check protein properties (UniProt)

📋 Clinical Evidence Review

Compile evidence for a hypothesis:

  1. Search trials (ClinicalTrials.gov)
  2. Find literature (PubMed)
  3. Check FDA data (OpenFDA)

📊 Literature Mining

Systematically search biomedical research:

  1. PubMed: 35M+ articles searchable by gene, disease, drug, chemical
  2. Preprints: bioRxiv, medRxiv
  3. Filter by keywords, date, study type

API Endpoint

Production (No setup needed):

https://mcp.cloud.curiloo.com/tools/unified/mcp

All 14+ databases unified into one endpoint.

Running Locally:

pip install medical-mcps
medical-mcps
# Available at: http://localhost:8000/tools/unified/mcp

Complete References

See detailed guides for each database:


Workflow Example

Complete Drug Repurposing Pipeline:

See drug-repurposing-workflow.md for step-by-step example with all 8 steps + curl commands.


API Keys

Most APIs are free, no key required. Optional keys for higher rate limits:

DatabaseKey?WhyGet Key
ChEMBLNoPublic data(not needed)
OpenTargetsNoPublic data(not needed)
PubMedNoPublic data(not needed)
ClinicalTrialsNoPublic data(not needed)
OMIMYesProprietary datahttps://omim.org/api
OpenFDAOptionalHigher rate limitshttps://open.fda.gov
NCI Clinical TrialsOptionalHigher rate limitshttps://clinicaltrialsapi.cancer.gov

Rate Limits & Caching

  • No authentication for production endpoint (public)
  • Rate limits: Generous (~1000+ requests/day per database)
  • Caching: Automatic 30-day HTTP caching (RFC 9111)
  • Cost: $0 (all databases public or researcher-accessible)

Common Patterns

Batch Query Loop

# Search multiple targets
for gene in CHRNE RAPSN LRP4; do
  curl -X POST https://mcp.cloud.curiloo.com/tools/unified/mcp \
    -H "Content-Type: application/json" -H "Accept: application/json" \
    -d "{\"jsonrpc\":\"2.0\",\"method\":\"tools/call\",\"params\":{\"name\":\"chembl_find_drugs_by_target\",\"arguments\":{\"target_name\":\"$gene\",\"max_results\":10}},\"id\":1}"
  sleep 1  # Be nice to the API
done

ID Conversion

Need to convert IDs between databases?

curl -X POST https://mcp.cloud.curiloo.com/tools/unified/mcp \
  -H "Content-Type: application/json" -H "Accept: application/json" \
  -d '{"jsonrpc":"2.0","method":"tools/call","params":{"name":"nodenorm_get_normalized_nodes","arguments":{"curie":"HGNC:11998"}},"id":1}'

Returns: Equivalent IDs in NCBI Gene, Uniprot, Ensembl, MyGene, etc.


Troubleshooting

No results?

  • Try alternative terms (gene symbol vs protein name)
  • Check spelling
  • Use standardized IDs (gene symbols, disease names)
  • Some APIs use specific ID formats (EFO vs MONDO, etc.)

Too many results?

  • Add filters (max_results, phase, recruitment status)
  • Use limit or size parameters
  • Combine with other databases to narrow focus

API key errors?

  • OMIM requires API key — get from https://omim.org/api
  • Other databases optional — request key if hitting rate limits

Next Steps

  1. Pick a use case (drug repurposing, target discovery, etc.)
  2. Read the relevant database guide from References section
  3. Copy a quick recipe from above
  4. Customize parameters for your disease/gene/drug
  5. Scale up — build your full research workflow

Resources

  • Source Code: https://github.com/pascalwhoop/medical-mcps
  • Author: Pascal Brockmeyer (@pascalwhoop)
  • Organization: Every Cure (https://www.everycure.org)
  • License: MIT

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